An excursion through quantitative model refinement

Sepinoud Azimi Rashti, Eugen Czeizler, Diana-Elena Gratie, Cristian Gratie, Bogdan Iancu, Ibssa Nebiat, Ion Petre, Vladimir Rogojin, Tolou Shadbahr, Fatima Shokri-Manninen

    Forskningsoutput: Kapitel i bok/konferenshandlingKonferensbidragVetenskapligPeer review

    Sammanfattning

    There is growing interest in creating large-scale computational models for biological process. One of the challenges in such a project is to fit and validate larger and larger models, a process that requires more high-quality experimental data and more computational effort as the size of the model grows. Quantitative model refinement is a recently proposed model construction technique addressing this challenge. It proposes to create a model in an iterative fashion by adding details to its species, and to fix the numerical setup in a way that guarantees to preserve the fit and validation of the model. In this survey we make an excursion through quantitative model refinement – this includes introducing the concept of quantitative model refinement for reaction-based models, for rule-based models, for Petri nets and for guarded command language models, and to illustrate it on three case studies (the heat shock response, the ErbB signaling pathway, and the self-assembly of intermediate filaments).
    OriginalspråkOdefinierat/okänt
    Titel på gästpublikationMembrane Computing
    RedaktörerGrzegorz Rozenberg, Arto Salomaa, José M. Sempere, Claudio Zandron
    FörlagSpringer
    Sidor25–47
    ISBN (elektroniskt)978-3-319-28475-0
    ISBN (tryckt)978-3-319-28474-3
    DOI
    StatusPublicerad - 2015
    MoE-publikationstypA4 Artikel i en konferenspublikation
    Evenemangconference - XV European Congress of Ichthyology
    Varaktighet: 1 jan 2015 → …

    Konferens

    Konferensconference
    Period01/01/15 → …

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